Text Classification
Transformers
PyTorch
distilbert
Generated from Trainer
Eval Results (legacy)
text-embeddings-inference
Instructions to use marcolatella/hate_trained_1234567 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use marcolatella/hate_trained_1234567 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="marcolatella/hate_trained_1234567")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("marcolatella/hate_trained_1234567") model = AutoModelForSequenceClassification.from_pretrained("marcolatella/hate_trained_1234567", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download training_args.bin from marcolatella/hate_trained_1234567: direct link, hf CLI and curl.
- Browser
- Download file 2.93 kB
-
https://huggingface.co/marcolatella/hate_trained_1234567/resolve/main/training_args.bin
- Command line
-
hf download hf://marcolatella/hate_trained_1234567/training_args.bin
-
curl -L -o training_args.bin https://huggingface.co/marcolatella/hate_trained_1234567/resolve/main/training_args.bin
2.93 kB
- Xet hash:
- 8671a91366e21271a61895bf1020440ace6611b31a71647fb63ef87b356f7b28
- Size of remote file:
- 2.93 kB
- SHA256:
- 611b92eddb5ed364c2eab2aee8814dc1fe7f0e608338f36926cb1cec0b15e88b
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